% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Senk:1015348,
      author       = {Senk, Johanna and Hagen, Espen and van Albada, Sacha and
                      Diesmann, Markus},
      title        = {{R}econciliation of weak pairwise spike-train correlations
                      and highly coherent local field potentials across space},
      journal      = {arXiv},
      publisher    = {arXiv},
      reportid     = {FZJ-2023-03672},
      year         = {2023},
      note         = {version 2 [2023]},
      abstract     = {Multi-electrode arrays covering several square millimeters
                      of neural tissue provide simultaneous access to population
                      signals such as extracellular potentials and spiking
                      activity of one hundred or more individual neurons. The
                      interpretation of the recorded data calls for multiscale
                      computational models with corresponding spatial dimensions
                      and signal predictions. Such models facilitate identifying
                      candidate mechanisms underlying experimentally observed
                      spatiotemporal activity patterns in the cortex. Multi-layer
                      spiking neuron network models of local cortical circuits
                      covering about 1 mm$^2$ have been developed, integrating
                      experimentally obtained neuron-type-specific connectivity
                      data and reproducing features of observed in-vivo spiking
                      statistics. Local field potentials (LFPs) can be computed
                      from the simulated spiking activity. We here extend a local
                      network and LFP model to an area of 4$\times$4 mm$^2$. The
                      upscaling preserves the densities of neurons while capturing
                      a larger proportion of the local synapses within the model.
                      The procedure further introduces distance-dependent
                      connection probabilities and conduction delays. Based on
                      model predictions of spiking activity and LFPs, we find that
                      the upscaling procedure preserves the overall spiking
                      statistics of the original model and reproduces asynchronous
                      irregular spiking across populations and weak pairwise
                      spike-train correlations in agreement with experimental data
                      recorded in the sensory cortex. In contrast with the weak
                      spike-train correlations, the correlation of LFP signals is
                      strong and decays over a distance of several hundred
                      micrometers, compatible with experimental observations.
                      Enhanced spatial coherence in the low-gamma band around 50
                      Hz may explain the recent experimental report of an apparent
                      band-pass filter effect in the spatial reach of the LFP.},
      keywords     = {Neurons and Cognition (q-bio.NC) (Other) / FOS: Biological
                      sciences (Other)},
      cin          = {INM-6 / IAS-6 / INM-10},
      cid          = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)IAS-6-20130828 /
                      I:(DE-Juel1)INM-10-20170113},
      pnm          = {5231 - Neuroscientific Foundations (POF4-523) / 5235 -
                      Digitization of Neuroscience and User-Community Building
                      (POF4-523) / HBP - The Human Brain Project (604102) / HBP
                      SGA1 - Human Brain Project Specific Grant Agreement 1
                      (720270) / SMHB - Supercomputing and Modelling for the Human
                      Brain (HGF-SMHB-2013-2017) / HBP SGA2 - Human Brain Project
                      Specific Grant Agreement 2 (785907) / HBP SGA3 - Human Brain
                      Project Specific Grant Agreement 3 (945539) / COBRA -
                      COmputing BRAin signals (COBRA): Biophysical computations of
                      electrical and magnetic brain signals $(250128_20200305)$ /
                      JL SMHB - Joint Lab Supercomputing and Modeling for the
                      Human Brain (JL SMHB-2021-2027) / DFG project 313856816 -
                      SPP 2041: Computational Connectomics (313856816) /
                      Brain-Scale Simulations $(jinb33_20121101)$ / Brain-Scale
                      Simulations $(jinb33_20191101)$ / Brain-Scale Simulations
                      $(jinb33_20220812)$},
      pid          = {G:(DE-HGF)POF4-5231 / G:(DE-HGF)POF4-5235 /
                      G:(EU-Grant)604102 / G:(EU-Grant)720270 /
                      G:(DE-Juel1)HGF-SMHB-2013-2017 / G:(EU-Grant)785907 /
                      G:(EU-Grant)945539 / $G:(Grant)250128_20200305$ /
                      G:(DE-Juel1)JL SMHB-2021-2027 / G:(GEPRIS)313856816 /
                      $G:(DE-Juel1)jinb33_20121101$ /
                      $G:(DE-Juel1)jinb33_20191101$ /
                      $G:(DE-Juel1)jinb33_20220812$},
      typ          = {PUB:(DE-HGF)25},
      doi          = {10.48550/arXiv.1805.10235},
      url          = {https://juser.fz-juelich.de/record/1015348},
}